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Volatility Mean-Reversion Strategy

Generates long/short/flat trading signals from historical volatility percentile rankings on OHLCV price data.

Source Download skill
Repository
HKUDS/Vibe-Trading
Stars
37,433
Licence
MIT
Files
2 files

What it does

Once installed, the agent can build a trading signal from price history using a volatility mean-reversion idea: it measures how volatile an asset has been recently (annualized standard deviation of returns), ranks that against the past few months, and marks periods of unusually low volatility as long (expecting volatility to rise) and unusually high volatility as exit or short (expecting it to fall). The skill also includes a small Python example engine that computes these signals with pandas.

Great for

  • Quant researchers prototyping simple volatility-based trading rules
  • Developers who want a readable pandas example of historical volatility percentile signals
  • Analysts backtesting how volatility regimes relate to later price moves

Skip it if

  • Live trading with real money: the skill gives a signal only, with no risk management, position sizing, costs or validation, and volatility is not a guarantee of direction (the skill itself says so)
  • Investment advice for people who are not able to evaluate backtests, since the output looks authoritative but is a simple rule

Try asking

  • “Compute 20-day historical volatility percentiles for BTC-USDT and give me long/short/flat signals”
  • “Apply the volatility strategy to my daily OHLCV CSV with a 120-day lookback and explain the parameters”
  • “Use 365 annualization for my crypto dataset and show the signal distribution”
Step-by-step guide: how to use Volatility Mean-Reversion StrategyInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 2 original files, the MIT licence and an attribution note.

    volatility.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip volatility.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip volatility.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Give the agent your own price data and ask it to report results on a backtest, not just the signal
  • Set annualize to 365 for crypto and 252 for equities, as the skill recommends
  • Ask the agent to check that the signal is 0 during the warm-up period before the lookback is filled

What's inside

  • example_signal_engine.py
  • SKILL.md

Redistributed unmodified from HKUDS/Vibe-Trading under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.